Table of Contents

LM Studio Setup

LM Studio is an open-source tool for running large language models locally. WindowSill supports LM Studio as an AI provider, giving organizations full control over their AI infrastructure without relying on cloud services.

Configuration Paths

WindowSill offers three ways to configure LM Studio, each with different network requirements and scenarios:

Scenario A: Administrators restrict AI providers and models to a defined list

Method Request Flow Network Requirement Best For
Dashboard App → WindowSill server → LM Studio LM Studio must be publicly accessible Centralized management, cloud-hosted LM Studio
WindowSill App App → LM Studio directly LM Studio reachable from user's device Centralized management while hosting LM Studio on a Private network or local installation

Scenario B: Administrators let user configure AI providers and models

Method Request Flow Network Requirement Best For
Registry App → LM Studio directly LM Studio reachable from user's device Per-organization member configuration, while using LM Studio on a Private network or local installation

Dashboard Configuration

When you configure LM Studio through the WindowSill Dashboard, all LLM requests are proxied through the WindowSill web server:

WindowSill App  →  WindowSill Server (getwindowsill.app)  →  Your public LM Studio Server

Requirements:

  • Your LM Studio server must be publicly accessible from the internet (with or without restrictions).
  • The WindowSill server IP (51.77.212.201) must be able to reach your LM Studio endpoint.
  • HTTPS is strongly recommended.

Advantages:

  • Centralized configuration for all organization members.
  • No client-side setup required.
  • LM Studio's endpoint is never stored on the client's machine.

Disadvantages:

  • You can not use an LM Studio server that is deployed on a private enterprise network or on user's local machine. The server has to be public on the internet.

How to configure (step-by-step)

  1. Navigate to WindowSill Dashboard.
  2. Select your organization and navigate to WindowSill tab, then AI Providers & Models.
  3. Change Configuration Mode to Restrict AI providers and models to a defined list.
  4. Click Add an AI Provider.
  5. Select LM Studio (public server)
  6. Enter the URL or IP address of your public LM Studio server, then click Add.
  7. Then, click Add Model and LM Studio (public server) to select the model(s) you want to allow your clients to use.

WindowSill App Configuration

When you configure LM Studio through the WindowSill App, the WindowSill app connects directly to your LM Studio server:

WindowSill App  → Your public, private or local LM Studio Server

Requirements:

  • Your LM Studio Server must be reachable directly from the client's machine. It can be done by either hosting LM Studio on the user's machine, deploying it on a private enterprise server, or a public server.

Advantages:

  • Centralized configuration for all organization members.
  • You can use an LM Studio server deployed on a private enterprise network or on user's local machine.
  • No internet exposure required.

Disadvantages:

  • If the list of models change on the LM Studio's server, or from a local machine to another, the WindowSill dashboard won't be aware of it until the configuration has been updated by an Administrator.
  • LM Studio's endpoint is always stored on the client's machine.

How to configure (step-by-step)

  1. Navigate to WindowSill Dashboard.
  2. Select your organization and navigate to WindowSill tab, then AI Providers & Models.
  3. Change Configuration Mode to Restrict AI providers and models to a defined list.
  4. On your Windows desktop, install and run the WindowSill app.
  5. Sign-in in the app using an organization Administrator account.
  6. Right-click on the WindowSill bar, Settings.
  7. Navigate to Account and ensure you select the Organization for which you want to edit the LM Studio's settings.
  8. Click Sync now to refresh your settings (just in case).
  9. Go to AI Writing & Analysis, AI Providers, WindowSill AI Pro.
  10. If you are administrator of the selected organization, you will see an Administrator Zone appearing at the bottom.
  11. Click Configure & Test LM Studio.
  12. Ensure the displayed organization name corresponds to the one you wish to edit.
  13. Enter your public, private network or local LM Studio server's endpoint, then click Connect
  14. If the connection was successfully established, enter an LLM prompt for test, select a model, then click Test. An LLM request will be send to the server. This is to ensure the WindowSill app can successfully interact with your potentially private or local LM Studio server.
  15. If the test was successful, click Upload Configuration to finish.
  16. Navigate back to WindowSill Dashboard. Refresh the page and navigate to WindowSill tab, then AI Providers & Models.
  17. Confirm that you see LM Studio (private network or local) listed in Providers, and that all the LM Studio's models are listed.
  18. Delete the model(s) you do not want to allow your clients to use.

Registry Configuration

When you configure LM Studio via Windows Registry, the WindowSill app connects directly to your LM Studio server:

WindowSill App  → Your public, private or local LM Studio Server

Requirements:

  • Your LM Studio Server must be reachable directly from the client's machine. It can be done by either hosting LM Studio on the user's machine, deploying it on a private enterprise server, or a public server.
  • Registry keys deployed via Group Policy, Intune, PowerShell or similar.

Advantages:

  • You can use an LM Studio server deployed on a private enterprise network or on user's local machine.
  • No internet exposure required.
  • Customization of the configuration is possible for each member of an organization.

Disadvantages:

  • No centralized configuration.
  • LM Studio's endpoint is always stored on the client's machine.

How to configure

See [Registry Keys](registry-keys.md#LM Studio) for configuration details.